Nama Mahasiswa: Nama Lengkap Anda
NIM: Nomor Induk Mahasiswa Anda
Tujuan Analisis: Dokumen ini bertujuan untuk mengeksplorasi dan menganalisis data melalui visualisasi, guna mendapatkan wawasan yang dapat mendukung pengambilan keputusan.
# Load library
library(ggplot2)
library(readxl)
# Baca dataset
df <- read_excel("Data.xlsx")
# Periksa nama kolom
colnames(df)
## [1] "geo" "Negara" "Benua"
## [4] "Tahun" "Angka_Harapan_Hidup" "Pendapatan_per_kapita"
## [7] "Populasi" "Jumlah_anak"
# Plot histogram
ggplot(df, aes(x = Angka_Harapan_Hidup)) +
geom_histogram(binwidth = 5, fill = "skyblue", color = "black") +
labs(
title = "Distribusi Angka Harapan Hidup",
x = "Angka Harapan Hidup",
y = "Frekuensi"
) +
theme_minimal()
# Scatter plot
ggplot(df, aes(x = Pendapatan_per_kapita, y = Angka_Harapan_Hidup)) +
geom_point(color = "blue", alpha = 0.7) +
labs(
title = "Hubungan Pendapatan per Kapita dan Angka Harapan Hidup",
x = "Pendapatan per Kapita",
y = "Angka Harapan Hidup"
) +
theme_minimal()
library(ggplot2)
ggplot(df, aes(x = Tahun, y = Negara, fill = Angka_Harapan_Hidup)) +
geom_tile() +
scale_fill_gradient(low = "blue", high = "red") +
labs(
title = "Heatmap Angka Harapan Hidup",
x = "Tahun",
y = "Negara",
fill = "Harapan Hidup"
) +
theme_minimal()
# Scatter plot interaktif
library(plotly)
##
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
##
## last_plot
## The following object is masked from 'package:stats':
##
## filter
## The following object is masked from 'package:graphics':
##
## layout
plot_ly(
df, x = ~Pendapatan_per_kapita, y = ~Angka_Harapan_Hidup,
type = "scatter", mode = "markers",
color = ~Benua, text = ~paste("Negara:", Negara)
)